{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Backtester Examples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "\n",
    "BACKTESTER_DIR = os.path.realpath(os.path.join(os.getcwd(), '..', '..'))\n",
    "TEST_DATA_DIR = os.path.join(BACKTESTER_DIR, 'backtester', 'test', 'test_data')\n",
    "SAMPLE_STOCK_DATA = os.path.join(TEST_DATA_DIR, 'test_data_stocks.csv')\n",
    "SAMPLE_OPTIONS_DATA = os.path.join(TEST_DATA_DIR, 'test_data_options.csv')\n",
    "\n",
    "sys.path.append(BACKTESTER_DIR) # Add backtester base dir to $PYTHONPATH"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sample backtest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from backtester import Backtest, Stock, Type, Direction\n",
    "from backtester.datahandler import HistoricalOptionsData, TiingoData\n",
    "from backtester.strategy import Strategy, StrategyLeg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we construct an options datahandler."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "options_data = HistoricalOptionsData(SAMPLE_OPTIONS_DATA)\n",
    "options_schema = options_data.schema"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we'll create a toy options strategy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_strategy = Strategy(options_schema)\n",
    "\n",
    "leg1 = StrategyLeg('leg_1', options_schema, option_type=Type.CALL, direction=Direction.BUY)\n",
    "leg1.entry_filter = ((options_schema.contract == 'SPX170317C00300000') &\n",
    "                     (options_schema.dte == 73)) | ((options_schema.contract == 'SPX170421C00500000') &\n",
    "                                                    (options_schema.dte == 51))\n",
    "\n",
    "leg1.exit_filter = (options_schema.dte == 44) | (options_schema.dte == 18)\n",
    "\n",
    "leg2 = StrategyLeg('leg_2', options_schema, option_type=Type.PUT, direction=Direction.BUY)\n",
    "leg2.entry_filter = ((options_schema.contract == 'SPX170317P00300000') &\n",
    "                     (options_schema.dte == 73)) | ((options_schema.contract == 'SPX170421P01375000') &\n",
    "                                                    (options_schema.dte == 51))\n",
    "\n",
    "leg2.exit_filter = (options_schema.dte == 44) | (options_schema.dte == 18)\n",
    "\n",
    "sample_strategy.add_legs([leg1, leg2])\n",
    "sample_strategy.add_exit_thresholds(profit_pct=0.2, loss_pct=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We do the same for stocks: create a datahandler together with a list of the stocks we want in our inventory and their corresponding weights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "stocks_data = TiingoData(SAMPLE_STOCK_DATA)\n",
    "stocks = [Stock('VOO', 0.4), Stock('TUR', 0.1), Stock('RSX', 0.5)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We set our portfolio allocation, i.e. how much of our capital will be invested in stocks, options and cash."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "allocation = {'stocks': 0.5, 'options': 0.5, 'cash': 0.0}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we create the `Backtest` object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "bt = Backtest(allocation, initial_capital=1_000_000)\n",
    "\n",
    "bt.stocks = stocks\n",
    "bt.stocks_data = stocks_data\n",
    "\n",
    "bt.options_strategy = sample_strategy\n",
    "bt.options_data = options_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And run the backtest with a rebalancing period of one month."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "0% [██████████████████████████████] 100% | ETA: 00:00:00\n",
      "Total time elapsed: 00:00:00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"7\" halign=\"left\">leg_1</th>\n",
       "      <th colspan=\"7\" halign=\"left\">leg_2</th>\n",
       "      <th colspan=\"3\" halign=\"left\">totals</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>contract</th>\n",
       "      <th>underlying</th>\n",
       "      <th>expiration</th>\n",
       "      <th>type</th>\n",
       "      <th>strike</th>\n",
       "      <th>cost</th>\n",
       "      <th>order</th>\n",
       "      <th>contract</th>\n",
       "      <th>underlying</th>\n",
       "      <th>expiration</th>\n",
       "      <th>type</th>\n",
       "      <th>strike</th>\n",
       "      <th>cost</th>\n",
       "      <th>order</th>\n",
       "      <th>cost</th>\n",
       "      <th>qty</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SPX170317C00300000</td>\n",
       "      <td>SPX</td>\n",
       "      <td>2017-03-17</td>\n",
       "      <td>call</td>\n",
       "      <td>300</td>\n",
       "      <td>195010.0</td>\n",
       "      <td>Order.BTO</td>\n",
       "      <td>SPX170317P00300000</td>\n",
       "      <td>SPX</td>\n",
       "      <td>2017-03-17</td>\n",
       "      <td>put</td>\n",
       "      <td>300</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Order.BTO</td>\n",
       "      <td>195015.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2017-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SPX170317C00300000</td>\n",
       "      <td>SPX</td>\n",
       "      <td>2017-03-17</td>\n",
       "      <td>call</td>\n",
       "      <td>300</td>\n",
       "      <td>-197060.0</td>\n",
       "      <td>Order.STC</td>\n",
       "      <td>SPX170317P00300000</td>\n",
       "      <td>SPX</td>\n",
       "      <td>2017-03-17</td>\n",
       "      <td>put</td>\n",
       "      <td>300</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>Order.STC</td>\n",
       "      <td>-197060.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2017-02-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SPX170421C00500000</td>\n",
       "      <td>SPX</td>\n",
       "      <td>2017-04-21</td>\n",
       "      <td>call</td>\n",
       "      <td>500</td>\n",
       "      <td>189250.0</td>\n",
       "      <td>Order.BTO</td>\n",
       "      <td>SPX170421P01375000</td>\n",
       "      <td>SPX</td>\n",
       "      <td>2017-04-21</td>\n",
       "      <td>put</td>\n",
       "      <td>1375</td>\n",
       "      <td>40.0</td>\n",
       "      <td>Order.BTO</td>\n",
       "      <td>189290.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2017-03-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SPX170421C00500000</td>\n",
       "      <td>SPX</td>\n",
       "      <td>2017-04-21</td>\n",
       "      <td>call</td>\n",
       "      <td>500</td>\n",
       "      <td>-185650.0</td>\n",
       "      <td>Order.STC</td>\n",
       "      <td>SPX170421P01375000</td>\n",
       "      <td>SPX</td>\n",
       "      <td>2017-04-21</td>\n",
       "      <td>put</td>\n",
       "      <td>1375</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>Order.STC</td>\n",
       "      <td>-185650.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2017-04-03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                leg_1                                                          \\\n",
       "             contract underlying expiration  type strike      cost      order   \n",
       "0  SPX170317C00300000        SPX 2017-03-17  call    300  195010.0  Order.BTO   \n",
       "1  SPX170317C00300000        SPX 2017-03-17  call    300 -197060.0  Order.STC   \n",
       "2  SPX170421C00500000        SPX 2017-04-21  call    500  189250.0  Order.BTO   \n",
       "3  SPX170421C00500000        SPX 2017-04-21  call    500 -185650.0  Order.STC   \n",
       "\n",
       "                leg_2                                                     \\\n",
       "             contract underlying expiration type strike  cost      order   \n",
       "0  SPX170317P00300000        SPX 2017-03-17  put    300   5.0  Order.BTO   \n",
       "1  SPX170317P00300000        SPX 2017-03-17  put    300  -0.0  Order.STC   \n",
       "2  SPX170421P01375000        SPX 2017-04-21  put   1375  40.0  Order.BTO   \n",
       "3  SPX170421P01375000        SPX 2017-04-21  put   1375  -0.0  Order.STC   \n",
       "\n",
       "     totals                  \n",
       "       cost  qty       date  \n",
       "0  195015.0  2.0 2017-01-03  \n",
       "1 -197060.0  2.0 2017-02-01  \n",
       "2  189290.0  2.0 2017-03-01  \n",
       "3 -185650.0  2.0 2017-04-03  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.run(rebalance_freq=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The trade log (`bt.trade_log`) shows we executed 4 trades: we bought 2 calls and 2 puts on _2017-01-03_ and _2017-03-01_, and exited those positions on _2017-02-01_ and _2017-04-03_ respectively."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The balance data structure shows how our positions evolved in time:\n",
    "- We started with $1000000 on _2017-01-02_\n",
    "- `total capital` is the sum of `cash`, `stocks capital` and `options capital`\n",
    "- `% change` shows the inter day change in `total capital`\n",
    "- `accumulated return` gives the compounded return in `total capital` since the start of the backtest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total capital</th>\n",
       "      <th>cash</th>\n",
       "      <th>VOO</th>\n",
       "      <th>TUR</th>\n",
       "      <th>RSX</th>\n",
       "      <th>options qty</th>\n",
       "      <th>calls capital</th>\n",
       "      <th>puts capital</th>\n",
       "      <th>stocks qty</th>\n",
       "      <th>options capital</th>\n",
       "      <th>stocks capital</th>\n",
       "      <th>% change</th>\n",
       "      <th>accumulated return</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-02</th>\n",
       "      <td>1.000000e+06</td>\n",
       "      <td>1000000.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-03</th>\n",
       "      <td>9.990300e+05</td>\n",
       "      <td>110117.405920</td>\n",
       "      <td>199872.763320</td>\n",
       "      <td>49993.281167</td>\n",
       "      <td>249986.549593</td>\n",
       "      <td>2.0</td>\n",
       "      <td>389060.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16186.0</td>\n",
       "      <td>389060.0</td>\n",
       "      <td>499852.594080</td>\n",
       "      <td>-0.000970</td>\n",
       "      <td>0.999030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>1.004228e+06</td>\n",
       "      <td>110117.405920</td>\n",
       "      <td>201052.238851</td>\n",
       "      <td>50072.862958</td>\n",
       "      <td>251605.333911</td>\n",
       "      <td>2.0</td>\n",
       "      <td>391380.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16186.0</td>\n",
       "      <td>391380.0</td>\n",
       "      <td>502730.435720</td>\n",
       "      <td>0.005203</td>\n",
       "      <td>1.004228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>1.002706e+06</td>\n",
       "      <td>110117.405920</td>\n",
       "      <td>200897.553535</td>\n",
       "      <td>49865.950301</td>\n",
       "      <td>250564.686850</td>\n",
       "      <td>2.0</td>\n",
       "      <td>391260.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16186.0</td>\n",
       "      <td>391260.0</td>\n",
       "      <td>501328.190686</td>\n",
       "      <td>-0.001516</td>\n",
       "      <td>1.002706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>1.003201e+06</td>\n",
       "      <td>110117.405920</td>\n",
       "      <td>201680.647945</td>\n",
       "      <td>49372.543196</td>\n",
       "      <td>248830.275081</td>\n",
       "      <td>2.0</td>\n",
       "      <td>393200.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16186.0</td>\n",
       "      <td>393200.0</td>\n",
       "      <td>499883.466222</td>\n",
       "      <td>0.000494</td>\n",
       "      <td>1.003201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-12</th>\n",
       "      <td>1.008599e+06</td>\n",
       "      <td>507298.036182</td>\n",
       "      <td>203126.836072</td>\n",
       "      <td>50621.271130</td>\n",
       "      <td>247552.567157</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16415.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>501300.674359</td>\n",
       "      <td>-0.002805</td>\n",
       "      <td>1.008599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-15</th>\n",
       "      <td>1.015904e+06</td>\n",
       "      <td>507298.036182</td>\n",
       "      <td>204154.459189</td>\n",
       "      <td>51695.869759</td>\n",
       "      <td>252755.284844</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16415.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>508605.613792</td>\n",
       "      <td>0.007243</td>\n",
       "      <td>1.015904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-16</th>\n",
       "      <td>1.014651e+06</td>\n",
       "      <td>507298.036182</td>\n",
       "      <td>204117.427725</td>\n",
       "      <td>51811.005327</td>\n",
       "      <td>251424.357064</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16415.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>507352.790116</td>\n",
       "      <td>-0.001233</td>\n",
       "      <td>1.014651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-17</th>\n",
       "      <td>1.005524e+06</td>\n",
       "      <td>507298.036182</td>\n",
       "      <td>200497.602152</td>\n",
       "      <td>50659.649653</td>\n",
       "      <td>247068.593419</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16415.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>498225.845224</td>\n",
       "      <td>-0.008995</td>\n",
       "      <td>1.005524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-18</th>\n",
       "      <td>1.001336e+06</td>\n",
       "      <td>507298.036182</td>\n",
       "      <td>201228.973560</td>\n",
       "      <td>49853.700681</td>\n",
       "      <td>242954.816643</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16415.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>494037.490883</td>\n",
       "      <td>-0.004165</td>\n",
       "      <td>1.001336</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            total capital            cash            VOO           TUR  \\\n",
       "2017-01-02   1.000000e+06  1000000.000000            NaN           NaN   \n",
       "2017-01-03   9.990300e+05   110117.405920  199872.763320  49993.281167   \n",
       "2017-01-04   1.004228e+06   110117.405920  201052.238851  50072.862958   \n",
       "2017-01-05   1.002706e+06   110117.405920  200897.553535  49865.950301   \n",
       "2017-01-06   1.003201e+06   110117.405920  201680.647945  49372.543196   \n",
       "...                   ...             ...            ...           ...   \n",
       "2017-05-12   1.008599e+06   507298.036182  203126.836072  50621.271130   \n",
       "2017-05-15   1.015904e+06   507298.036182  204154.459189  51695.869759   \n",
       "2017-05-16   1.014651e+06   507298.036182  204117.427725  51811.005327   \n",
       "2017-05-17   1.005524e+06   507298.036182  200497.602152  50659.649653   \n",
       "2017-05-18   1.001336e+06   507298.036182  201228.973560  49853.700681   \n",
       "\n",
       "                      RSX  options qty  calls capital  puts capital  \\\n",
       "2017-01-02            NaN          NaN            NaN           NaN   \n",
       "2017-01-03  249986.549593          2.0       389060.0           0.0   \n",
       "2017-01-04  251605.333911          2.0       391380.0           0.0   \n",
       "2017-01-05  250564.686850          2.0       391260.0           0.0   \n",
       "2017-01-06  248830.275081          2.0       393200.0           0.0   \n",
       "...                   ...          ...            ...           ...   \n",
       "2017-05-12  247552.567157          0.0            0.0           0.0   \n",
       "2017-05-15  252755.284844          0.0            0.0           0.0   \n",
       "2017-05-16  251424.357064          0.0            0.0           0.0   \n",
       "2017-05-17  247068.593419          0.0            0.0           0.0   \n",
       "2017-05-18  242954.816643          0.0            0.0           0.0   \n",
       "\n",
       "            stocks qty  options capital  stocks capital  % change  \\\n",
       "2017-01-02         NaN              0.0        0.000000       NaN   \n",
       "2017-01-03     16186.0         389060.0   499852.594080 -0.000970   \n",
       "2017-01-04     16186.0         391380.0   502730.435720  0.005203   \n",
       "2017-01-05     16186.0         391260.0   501328.190686 -0.001516   \n",
       "2017-01-06     16186.0         393200.0   499883.466222  0.000494   \n",
       "...                ...              ...             ...       ...   \n",
       "2017-05-12     16415.0              0.0   501300.674359 -0.002805   \n",
       "2017-05-15     16415.0              0.0   508605.613792  0.007243   \n",
       "2017-05-16     16415.0              0.0   507352.790116 -0.001233   \n",
       "2017-05-17     16415.0              0.0   498225.845224 -0.008995   \n",
       "2017-05-18     16415.0              0.0   494037.490883 -0.004165   \n",
       "\n",
       "            accumulated return  \n",
       "2017-01-02                 NaN  \n",
       "2017-01-03            0.999030  \n",
       "2017-01-04            1.004228  \n",
       "2017-01-05            1.002706  \n",
       "2017-01-06            1.003201  \n",
       "...                        ...  \n",
       "2017-05-12            1.008599  \n",
       "2017-05-15            1.015904  \n",
       "2017-05-16            1.014651  \n",
       "2017-05-17            1.005524  \n",
       "2017-05-18            1.001336  \n",
       "\n",
       "[96 rows x 13 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.balance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Statistics and Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from backtester.statistics import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Summary table of our options strategy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fdd\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Strategy</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddlevel0_row0\" class=\"row_heading level0 row0\" >Total trades</th>\n",
       "                        <td id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddrow0_col0\" class=\"data row0 col0\" >2</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddlevel0_row1\" class=\"row_heading level0 row1\" >Number of wins</th>\n",
       "                        <td id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddrow1_col0\" class=\"data row1 col0\" >1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddlevel0_row2\" class=\"row_heading level0 row2\" >Number of losses</th>\n",
       "                        <td id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddrow2_col0\" class=\"data row2 col0\" >1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddlevel0_row3\" class=\"row_heading level0 row3\" >Win %</th>\n",
       "                        <td id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddrow3_col0\" class=\"data row3 col0\" >50.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddlevel0_row4\" class=\"row_heading level0 row4\" >Largest loss</th>\n",
       "                        <td id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddrow4_col0\" class=\"data row4 col0\" >$7280.00</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddlevel0_row5\" class=\"row_heading level0 row5\" >Profit factor</th>\n",
       "                        <td id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddrow5_col0\" class=\"data row5 col0\" >1.00</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddlevel0_row6\" class=\"row_heading level0 row6\" >Average profit</th>\n",
       "                        <td id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddrow6_col0\" class=\"data row6 col0\" >$-1595.00</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddlevel0_row7\" class=\"row_heading level0 row7\" >Average P&L %</th>\n",
       "                        <td id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddrow7_col0\" class=\"data row7 col0\" >0.00%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddlevel0_row8\" class=\"row_heading level0 row8\" >Total P&L %</th>\n",
       "                        <td id=\"T_ae9adb42_6a2e_11ea_9301_38f9d3530fddrow8_col0\" class=\"data row8 col0\" >99.68%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x11424c8d0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary(bt.trade_log, bt.balance)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot of the accumulated returns over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "</script>"
      ],
      "text/plain": [
       "alt.VConcatChart(...)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "returns_chart(bt.balance)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Daily returns histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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